Bayes Theorem: Difference between revisions
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imported>Robert Badgett (New page: '''Bayes Theorem''' is defined as "a theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people...) |
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'''Bayes Theorem''' is defined as "a theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihoods of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result".<ref name="MeSH">{{cite web |url=http://www.nlm.nih.gov/cgi/mesh/2008/MB_cgi?mode= |title=Bayes Theorem |accessdate=2007-12-09 |author=National Library of Medicine |authorlink= |coauthors= |date= |format= |work= |publisher= |pages= |language= |archiveurl= |archivedate= |quote=}}</ref> | '''Bayes Theorem''' is defined as "a theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihoods of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result".<ref name="MeSH">{{cite web |url=http://www.nlm.nih.gov/cgi/mesh/2008/MB_cgi?mode= |title=Bayes Theorem |accessdate=2007-12-09 |author=National Library of Medicine |authorlink= |coauthors= |date= |format= |work= |publisher= |pages= |language= |archiveurl= |archivedate= |quote=}}</ref> | ||
==Calculations== | |||
<!-- http://www.memory-alpha.org/en/wiki/Help:Math_markup --> | |||
:<math>\mbox{Sensitivity of a test} =\left (\frac{\mbox{Total with a positive test}}{\mbox{Total }with\mbox{ disease}}\right )</math> | |||
:<math>\mbox{Specificity of a test}=\left (\frac{\mbox{Total with a negative test}}{\mbox{Total }without\mbox{ disease}}\right )</math> | |||
:<math>\mbox{Positive predictive value}=\left (\frac{\mbox{Total }with\mbox{ disease and a positive test}}{\mbox{Total with a positive test}}\right )</math> | |||
:<math>\mbox{Negative predictive value}=\left (\frac{\mbox{Total }without\mbox{ disease and a negative test}}{\mbox{Total with a negative test}}\right )</math> | |||
==References== | ==References== | ||
Revision as of 06:24, 9 December 2007
Bayes Theorem is defined as "a theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihoods of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result".[1]
Calculations
References
- ↑ National Library of Medicine. Bayes Theorem. Retrieved on 2007-12-09.